1. WMO SDS-WAS Research and Development activities 8th meeting of the WWRP SSC (WMO Headquarters, Geneva, 24-27 November 2015) S. Nickovic (SDS-WAS NAMEE, Serbia) E. Terradellas SDS-WAS NAMEE (AEMET, Spain) 8th meeting of the WWRP SSC (WMO Headquarters, Geneva, 24-27 November 2015)

2. 2 SDS-WAS Mission To enhance the ability of countries to deliver timely and quality sand and dust storm forecasts, observations, information and knowledge to users through an international partnership in research and operations

3. 3 Outreach/publications

4. test footer 4 Major SDS-WAS Regional activities/meetings NAMEE Centre September 2015, Sofia: participation in a meeting of the Joint WWRP/WGNE Working Group (WG) on Forecast Verification Research held in. October, 2015, Ankara: participation in the side event ‘The edge of crisis: Sand and dust storms’ during the 12th Conference of the Parties of the United Nations Convention to Control Desertification (UNCCD). WMO and UNEP to assess the extent and impacts of SDS globally. November 2015 Amman: Organization of WMO/WHO/UNEP/EUMETSAT/AEMET ‘1st Africa / Middle East Expert Meeting and Workshop on the Health Impact of Airborne Dust’ PANAMCentre Installing the Pan-America Center for the SDS-WAS within the Caribbean Institute for Meteorology and Hydrology (CIMH) in Barbados

5. WWRP IP Transition to operational activities Regional Specialized Meteorological Center with activity specialization on Atmospheric Sand and Dust Forecast (RSMC-ASDF) (Barcelona Dust Forecast Center) enables daily dust forecasts; Operational from 2014 The Asian region plans a center of the same kind

6. 6 WWRP IP: to work with WCRP towards scientific studying on the impact of climate change on high impact weather events SDS-WAS dust reanalysis project: dust reanalysis 1979-2010 using the BSC dust model (horizontal 0.5x0.5deg; 40 vertical layers) Burkina Faso, Mali, Niger, Chad: average surface dust C, 2005-2010 average surface dust C, MAM, 1979-2010

7. 7 WWRP IP:...to develop coupled modeling for applications SDS-WAS plans To develop coupled models with integrated dust-atmosphere -direct and - indirect (clouds) feedback mechanisms at regional and regional scale WGs: WCRP, S2S, Mesoscale, MACC CMA dust-radiation feedback OBS CTRLRAD DIRECT FEEDBACKS MACC dust-radiation feedback T difference (Remy et al, 2014 ACP)

8. DeMott et al., 2003 Cziczo et al, 2013, Science Dust: the best agent for cold cloud generation 2/3 of ice clouds formed due to pure dust and dust metallic oxides Small # of dust particles needed to triger the process Heterogeneous freezing dominant Ice formation Koop and Mahowald, Nature, 2013 WWRP IP:...to develop coupled modeling for applications CLOUD-DUST FEEDBACKS

9. 9 WWRP IP:...to develop coupled modeling for applicationsCLOUD-DUST FEEDBACKS #IN parameterization in dust models Niemand et al, 2012: COSMO #IN simulation Nickovic et al, 2015: DREAM #IN simulation MSG IWP MODIS IWP DREAM IWP DREAM vs. Potenza Radar cloud ice Hande et al, 2015 COSMO #IN climatology Serbian HMS will launch in Dec 2015 experimental daily predictions of #IN due to dust using DREAM model

10. Tehran 10 WWRP IP: To predict high impact weather on wider time ranges, WWRP to coordinate with WCRP, GFCS, relevant commissions, the regional associations, NMHSs, WMO Programmes. Emphasis: Development of seamless prediction strategy SDS-WAS plans Dust modelling - predicting the process in a seamless manner - from very short-term (day or shorter) to medium and climate 2yr plan – model resolutions <10km in regional and <20km in global models 8yr plan – model resolutions <3km in regional and <10km in global models SDS-WAS PROJECT: Tehran 2014 SDS case – high resolution modelling (res <3km) Phoenix Jul 2011 “haboob”(res ~4km) Vukovic et al, 2013, ACP Pejanovic et al, 2015, unpublished Phoenix

11. 11 WWRP IP WWRP and GAW to pay special attention to nonconventional observations and how these could be used through - sophisticated data assimilation techniques as input to ultra high resolution models and - verification of predictions. ASSIMILATION

12. 12 CMA : FY-2D satellite data assimilation KMA: MODIS AOD assimilation Plans: 2yrs: to further improve current assimilation methods 5yrs: include lidars/CALIPSO data ASSIMILATION

13. 13 RHMSS, Serbia &; NOA, Athens (assimilation in DREAM model) UK MetOffice (SIVIRI/MSG AOD) Finokalia Lidar OBS Jun/Jul 2014 Z-T graph Finokalia model Jun/Jul 2014 Z-T graph ASSIMILATION

14. 14 MODEL VALIDATION NAMEE daily, monthy, seasonal and annual Validations of models against AERONET AOD WGs: GAW; SAG Aerosol

15. 15 Near real time model validation against ground-based and satellite data in Asian Centre (CMA) Near real time model validation against ground-based and satellite data in Asian Centre (CMA) MODEL VALIDATION

16. 16 Non-conventional observations

17. 17 Non-conventional observations Ceilometer data to be used in the future for aersol/dust assimilation (below: DWD evidence on the ceil. network)

18. 18 WWRP IP...need to better understand fundamental processes that determine the interactions between environmental sub-systems

19. 19 WWRP IP... to develop user-orientated indices for HI weather events; quantify predictives skills...... SDS-WAS to addres air quality and health impacts in particular SDS WAS COST proposal "European Network for Use of Information on Atmospheric Dust Monitoring and Forecasting“ - Addressed to health stakeholders: to better understand the dust impact on human health. To develop user products appropriate for alerting the population during the most serious SDS. - Addressed to meteorological and climate services: to better understand the dust-cloud-radiation interactions allowing improved radiation and clouds parameterizations in NWP and climate models. - Addressed to aviation operators: to achieve precise forecasts of visibility reduction by dust particles which can improve air traffic management and safety.

20. 20 Amman, Jordan, 2-5 November 2015 WWRP IP SDS-WAS to addres air quality and health impacts in particular -Addressed to solar power generation sector: to better assess investments in new infrastructures by predicting impact of reduced radiation operational plants and to plan maintenance and cleanup tasks. -Addressed to fishery industry: to receive estimates of deposited dust as nutrient responsible for increasing marine productivity in specific areas. - Addressed to air quality agencies: reporting of PM10 episodes related to dust events.

21. 21 WWRP IP involve operational forecasters in HI Weather interpretation. Training BSC Centre training events EUMETCast dissemination of dust forecasts 2015 Portal end-user documentation 4th Training course on WMO SDS-WAS products (satellite and ground observation and modelling of atmospheric dust) (Casablanca, Morocco, 17-20 Nov 2014) Training course on the use of satellite products for agrometeorological applications (Addis-Ababa, Ethiopia, 23- 27 Mar 2015)

22. www.wmo.int Thank you